Abstract
This paper briefly describes the methods available for collection, atmospheric and geometric correction, and processing of hyperspectral imagery. Discussion of data capture concentrates on logistics of integrating image acquisition with field data collection. Atmospheric correction is required to use the imagery with reference spectra from field and laboratory sensors; a variety of methods for atmospheric correction are described. Geometric correction is required for integration of the image data and derived products with other geographic information. A description of methods for single and multiple feature identification is provided. These all focus on the analysis of the spectral description of surface materials provided by hyperspectral imagery; methods for multiple feature identification take advantage of high spectral dimensionality of the imagery to identify sub-pixel components. A role for spatial analysis combined with spectral analysis in interpretation of environmental features is identified.
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